1. No category

Hoeschele M, Merchant H, Kikuchi Y, Hattori Y, ten Cate C.
Searching for the origins of musicality across species.
Philosophical Transactions B 2015, 370(1664): 20140094.
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Searching for the origins of musicality
across species
rstb.royalsocietypublishing.org
Marisa Hoeschele1, Hugo Merchant2, Yukiko Kikuchi3, Yuko Hattori4
and Carel ten Cate5,6
1
Review
Cite this article: Hoeschele M, Merchant H,
Kikuchi Y, Hattori Y, ten Cate C. 2015 Searching
for the origins of musicality across species. Phil.
Trans. R. Soc. B 370: 20140094.
http://dx.doi.org/10.1098/rstb.2014.0094
One contribution of 12 to a theme issue
‘Biology, cognition and origins of musicality’.
Subject Areas:
behaviour, cognition, neuroscience, evolution,
ecology
Keywords:
musicality, music perception, evolution of
music, animal models, comparative studies
Department of Cognitive Biology, Vienna, Austria
Instituto de Neurobiologia, UNAM, Campus Juriquilla, Santiago de Quere´taro, Mexico
3
Institute of Neuroscience, Newcastle University Medical School, Newcastle upon Tyne, UK
4
Primate Research Institute, Kyoto University, Kyoto, Japan
5
Institute of Biology, and 6Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
2
In the introduction to this theme issue, Honing et al. suggest that the origins
of musicality—the capacity that makes it possible for us to perceive, appreciate and produce music—can be pursued productively by searching for
components of musicality in other species. Recent studies have highlighted
that the behavioural relevance of stimuli to animals and the relation of experimental procedures to their natural behaviour can have a large impact on the
type of results that can be obtained for a given species. Through reviewing
laboratory findings on animal auditory perception and behaviour, as well as
relevant findings on natural behaviour, we provide evidence that both traditional laboratory studies and studies relating to natural behaviour are
needed to answer the problem of musicality. Traditional laboratory studies
use synthetic stimuli that provide more control than more naturalistic
studies, and are in many ways suitable to test the perceptual abilities of animals. However, naturalistic studies are essential to inform us as to what
might constitute relevant stimuli and parameters to test with laboratory
studies, or why we may or may not expect certain stimulus manipulations
to be relevant. These two approaches are both vital in the comparative
study of musicality.
Author for correspondence:
Marisa Hoeschele
e-mail: [email protected]
1. Introduction
Honing et al. [1] suggest that the origins of musicality—the capacity that makes
it possible for us to perceive, appreciate and produce music—can be pursued
productively by searching for components of musicality in other species.
Perhaps the most obvious starting point in this endeavour is the examination
of animal responses to music. In 1984, Porter & Neuringer [2] were the first
to conduct an experiment from this perspective by training pigeons (Columba
livia) to discriminate the music of different composers. The authors used an
operant paradigm, where pigeons received a food reward after pecking one
of two discs during presentation of excerpts from several Bach pieces for
organ and Stravinsky’s Rite of spring. Pigeons were trained to respond to the
left disc during Bach, and a right disc during Stravinsky excerpts. With time,
the pigeons learned this discrimination. Once the pigeons were making few
errors, they were presented with novel excerpts from the same composers,
and similar excerpts from other composers. The pigeons generalized to all of
these novel stimuli through their responses to the two choice discs in a way
that mirrored that of human participants.
A more recent study was performed using a similar operant paradigm with
carp (Cyprinus carpio) using blues and classical stimuli and found comparable
results [3]; after initial training with a small set of blues and classical music
stimuli, carp were able to correctly classify stimuli from these genres that
they had never heard before. How can we interpret the fact that distantly
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2. Key problems in studying biomusicology
3. Traditional laboratory studies
There is much debate about the relative utility of naturalistic
and artificial laboratory studies. Proponents of naturalistic
studies argue that training animals to perform ‘unnatural’
behaviours, or using stimuli that differ markedly from those
in their natural environment, does not constitute an appropriate comparison for human behaviours that emerge without
training. They also point out that artificial stimuli can result
in underestimation of animal abilities. Proponents of laboratory research note that experimental control and systematic
comparisons across species may reveal underlying abilities
and potential that are not apparent in natural behaviour. As
a result, laboratory studies can shed light on the presence
of cognitive abilities that support such behaviour as well as
their biological basis. Both sides have valid insights about the
limitations of the other approach, but they fail to appreciate
its strengths and the utility of combined approaches. For
example, much has been gained from studying behavioural
and neural processes in various species in response to artificial
auditory patterns presented in laboratory settings.1
(a) Rhythm
The processing of auditory rhythms—both the underlying
pulse or beat and the organization of the beats into repetitive
groups—relies on basic features of the auditory system. The
use of operant conditioning procedures has revealed greater
temporal sensitivity in birds than in humans [13] when evaluating perceptual differences among brief stimuli. In another
study [14], pigeons successfully learned to differentiate two
metrical patterns (8/4 versus 3/4) and to transfer the discrimination to different tempos, but their learning did not generalize
to metrical patterns in a different timbre. In addition, they had
difficulty differentiating rhythmic sequences from random
sequences. European starlings, however, learned to differentiate rhythmic from non-rhythmic sequences and showed a
broader range of generalization [15].
1
For definitions of musical terms, please see the glossary, table 1.
2
Phil. Trans. R. Soc. B 370: 20140094
The genre classification performance of pigeons and carp has
an analogue in studies on visual categorization. In their seminal study, Hernnstein & Loveland [4] successfully trained
pigeons to discriminate photos that contained humans from
photos that did not, with all photos exhibiting considerable
variability. Subsequent debate has centred on whether the
pigeons were detecting humans or simply using local features (e.g. large flesh-coloured area) to solve the task [5].
Similarly, pigeons and carp in the music categorization
tasks may use specific local features (e.g. presence of absence
of a specific frequency) rather than use global or abstract features to solve the task. One way to determine what features
are controlling the behaviour in each species would be to present altered stimuli that are missing some of the features from
the rich training stimuli or present some features of the rich
stimuli in isolation.
A second, and equally important issue, is motivational.
Aside from the music categorization abilities demonstrated in
pigeons and carp, do they have any music preferences? We
know that chimpanzees prefer at least some types of music to
silence, as they spent more time close to a speaker when
music was being played than when it was not [6]. But another
primate species not as closely related to humans, the cotton-top
tamarins (Saguinus oedipus), showed the opposite result [7].
Several other studies have looked at animal musical preferences using similar place preference paradigms. Chiandetti
& Vallortigara [8] put newborn chicks (Gallus gallus) in an
environment with consonant music playing on one side, and
dissonant music on the other. They found that the chicks
spent more time on the side with consonant music. When
McDermott & Hauser [9] presented cotton-top tamarins with
consonant stimuli in one arm of a Y-maze and dissonant
stimuli in the other arm, the animals showed no preference.
Western adults confronted with similar contingencies spent
more time listening to consonant than to dissonant sounds.
Although such a preference paradigm suggests that a feature
such as consonance and dissonance is relevant to a given
species, it tells us little about the mechanisms underlying any
preferences. The human preference for consonance over dissonance is at least partially based on the physical properties of
sound and is evident across many cultures [10]. It is equally
important to ascertain the factors contributing to music-related
preferences in non-human species.
Another problem is the selection of appropriate species
for study. Taking a traditional laboratory approach, it is possible to take virtually any species with sound-sensing capacity
and rudimentary learning capacities and measure its physiology and train it to discriminate different sounds. But
which species are relevant for biomusicology? One approach
is to study species based on shared ancestry. Species that are
closely related to humans are likely to share some of our abilities, and are therefore good models for experiments that
would be difficult to conduct in humans. For traits that are
not shared among closely related species, it is easier to pinpoint the differences in underlying mechanisms. Species
that are more distantly related sometimes share traits without
sharing a common ancestor with those traits. By examining the
evolutionary convergence between these non-related species,
we can identify biological constraints or mechanisms required
for that trait and the selection pressures giving rise to it. For
example, some of the traits that are considered highly relevant
for biomusicology to date are vocal learning and entrainment.
Vocal learning involves the ability to produce vocalizations
based on auditory input, and entrainment involves the ability
to synchronize movements with an external stimulus (usually
sound). Both traits are uncommon in non-human species but
shared across some unrelated species, so their study could provide clues to their nature and possible interaction [11,12]. Thus,
both approaches, examining closely related and distantly
related species, can be quite useful for probing the biological
basis of musicality.
Thus, we need to consider the perceptual abilities of animals, their natural preferences, as well their similarity to
humans in terms of phylogeny or shared traits. This task
necessitates the combined fruits of traditional laboratory
studies with artificial stimuli and more naturalistic studies.
rstb.royalsocietypublishing.org
related animal species have human-like boundaries for the
categorization of such complex auditory stimuli? Moreover,
what can we learn from such studies?
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Table 1. Glossary of relevant musical terms.
beat
the underlying pulse, or unit of time, in music
entrainment
the ability to perceive a beat in music and align
bodily movement with it
melody
a sequence of tones defined by its pitch
patterning and rhythm
meter
the recurring pattern of stressed and unstressed
beats in music
musicality
the capacity that underlies the human ability to
pitch
perceive, appreciate, and produce music
a perceptual attribute related to the fundamental
frequency that enables comparisons of sounds
as higher or lower
prosody
rhythm, loudness, pitch, and tempo of speech
rhythm
a non-random repetitive temporal auditory
pattern
timbre
the quality of musical sound that distinguishes
different sound sources such as voices and
vocal learning
specific musical instruments
long-term modification of vocal production by
imitation
The use of neurophysiological (e.g. functional magnetic resonance imaging, fMRI) measures has revealed that the neural
substrates of sequencing and timing behaviours overlap with
those related to human music perception and performance (see
[16] for a review) and that the motor corticobasal ganglia–
thalamocortical circuit (mCBGT) plays an important role
[17–19]. Not only are trained rhesus macaques (Macaca mulatta)
capable of interval timing and motor sequencing tasks performed by humans [20–24], but they also show similar neural
activation in mCBGT in both sequential [25,26], and single interval timing tasks [27–29]. These results suggest that the role of
mCBGT in auditory rhythm processing is shared across these
two species of primates. Uncovering findings such as these
was only possible with the use of artificial laboratory probing
of the limits of the perceptual systems of these two species.
(b) Timbre
Timbre perception has not received much attention in the
animal literature, but laboratory studies have begun to provide
some insights. As with temporal intervals, avian species seem
to detect more fine-grained timbral differences than humans do
[30–32]. Timbre is considered a surface [33] feature, because
humans recognize the same musical patterns, regardless of
the timbre of presentation (e.g. vocal, piano, flute). This ability
to generalize across timbres is reportedly present from the newborn period [34]. In one study, humans’ responses to chords
readily generalized across timbres, but that was not the case
with black-capped chickadees (Poecile atricapillus) [35]. Zebra
finches exhibit generalization across timbres [36,37]. When
trained to discriminate between two words produced by
male (or female) speakers, they showed generalization across
(c) Pitch
The pitch of a sound is typically based on the fundamental
frequency of that sound [38], although human listeners can
perceive the pitch of a sound in which the fundamental frequency is missing [39]. The ability to perceive the so-called
missing fundamental is present in infants as young as three
months of age [40] and is also demonstrable in cats (Felis
catus [41]), rhesus monkeys [42] and starlings [43]. The
assumption is that this ability is shared across species, but
its generality has not been established empirically.
Listeners sometimes evaluate fundamental frequency or
pitch in an absolute manner, as when musicians with absolute
pitch correctly name the pitch class of musical notes (e.g. 440 Hz
as A) [44] or non-musicians distinguish the original pitch level
of highly familiar recorded music from versions that have been
shifted by one or two semitones [45]. In general, birds are
superior to mammals at detecting absolute pitch ([46–48],
but see [49]). In most cases, however, human listeners focus
on relations among pitches rather than absolute pitch levels
while listening to music. In musical contexts, moreover,
human listeners exhibit octave generalization, perceiving the
similarity of notes that are one or more octaves apart [50,51].
The evidence for octave generalization in non-human species
is both limited and controversial. Blackwell & Schlosberg [52]
claimed that rats (Rattus norvegicus) generalized from training
stimuli in one octave to test stimuli in another octave. However,
there are alternative explanations of the findings, because the
stimuli may have contained harmonics that provided common
cues across octaves [50]. Suggestive evidence for octave generalization comes from a bottlenose dolphin (Tursiops truncatus) that
mimicked sounds outside of her vocal range by reproducing
them an octave apart from the original [53]. Interestingly,
rhesus monkeys trained to differentiate melodies in a same–
different task responded to octave-transposed melodies as
‘same’ for Western tonal, but not atonal melodies [54].
To date, there is no evidence of octave generalization in
avian species. Cynx [55] trained starlings to discriminate
between two tones, and then tested whether they generalized
this discrimination to the octave. They did not. The failure of
human listeners to exhibit octave generalization on the same
task [56] called the starling findings into question. In a similar
operant training task, humans exhibited octave generalization
[56], but an adaptation of the task for black-capped chickadees
revealed no octave generalization [57]. The available evidence
is consistent with the absence of octave generalization in birds,
but more laboratory research is needed with a wider range of
species before the question can be resolved definitively.
With regards to relative pitch, several studies have found
that non-human animals could be trained to discriminate
among chords (i.e. simultaneous combinations of tones):
European starlings [58], Java sparrows (Lonchura oryzivora;
[59]), Japanese monkeys (Macaca fuscata; [60]), pigeons [61]
and black-capped chickadees [35,62]. All of these studies
ensured the animals were not simply memorizing the absolute properties of the sounds by presenting novel stimuli with
identical or similar relative pitch properties but different
absolute pitches. All species were able to transfer what they
learned to these novel stimuli.
Phil. Trans. R. Soc. B 370: 20140094
definition
3
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term
speaker gender (i.e. fundamental frequency and spectral differences). Clearly, more research is needed to clarify the nature
and extent of timbre generalization across species.
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Building on the foundations of the auditory system and
interval timing is the perception of grouping. Gestalt psychologists noted long ago that a group of visual or auditory
elements has qualities that are more than the sum of its parts.
A repeated series of tones of equal frequency and amplitude,
with one tone having longer duration than the others, is perceived as an iambic pattern in which the long sound marks
the end of a sound unit [73]. A repeated series of tones in
which one tone has higher frequency or amplitude than the
others is perceived as a trochaic pattern in which the higher
pitched or louder sound marks the beginning of the sound
unit [73]. This type of patterning is common in music as well
as speech and young infants seem to spontaneously recognize
trochaic patterns [74]. Rats seem to group tones according to
trochaic, but not iambic rules [75], which indicates that such
grouping abilities are not exclusive to human listeners. Further
research is needed to explore the nature of auditory grouping
abilities across species.
The ability to perceive higher-order temporal patterns in a
stream of sounds is relevant to speech as well as music perception. The perception of speech prosody, or the melody of
speech, is relevant to music perception. In many languages,
for example, statements end with a falling terminal pitch contour, and yes/no questions end with a rising terminal pitch
(e) Criticisms of laboratory studies
When non-human animals are trained to discriminate auditory patterns, they typically take a lot longer to learn the
task than their human counterparts. A critic may ask, for
example, whether a bird trained for hundreds of trials to discriminate chords can really be compared with a human who
discriminates the chords without training or with minimal
training. That situation does not negate the value of comparisons of music perception in human and non-human listeners.
Although human listeners may require little training for
specific tasks, they have had years of exposure to music
and have a wealth of implicit musical knowledge. Moreover,
the ability of non-human listeners to perform certain tasks,
even after extensive training, can provide insights into the
mechanisms underlying that ability.
Consider the studies of interval timing in rhesus macaques and humans. As the interaction between the auditory
stimulus and required motor output becomes more complex,
monkeys’ performance lags increasingly behind that of
humans. In one study, monkeys and humans were required
to tap on a push-button to produce six isochronous intervals
in a sequence. An auditory stimulus was present to guide
tapping during the first three taps but not the last three,
which required internal timing based on the preceding auditory stimulus or taps [20,82]. Although monkeys produced
rhythmic movements with appropriate tempo matching,
their movements lagged by approximately 250 ms after each
auditory stimulus, even after long periods of training (close
to a year; [20]). In contrast, humans easily perform the same
task, with no training, showing stimulus movement asynchronies approaching zero or with negative values [20,83]. Such
differences in two closely related species make it possible to
predict that the mCBGT may have subtle, but critical differences that evolved in order to process complex auditory
information and use it in a predictive fashion to control the
temporal and sequential organization of movement, as recently
stated in the gradual audiomotor evolution hypothesis [84].
Even if humans and monkeys had comparable experience
with the stimuli in such experimental tasks, which they do
not, both have very different interpretations of the experimental context and the experimenter’s intentions, even
where efforts have been made to minimize differences in
training requirements and outcomes [35,49,57,62].
(f ) Conclusions
Overall, the aforementioned evidence indicates the enormous
potential of laboratory studies of some components of musicality with non-human species. Operant conditioning studies
have the potential to reveal skills that are not part of an
animal’s natural repertoire. Animals’ performance in these
tasks is deeply rooted in the limitations and adaptive
4
Phil. Trans. R. Soc. B 370: 20140094
(d) High-order acoustic patterns
contour [76]. Different languages also have different prosodic
patterns [77]. Tamarins [78], rats [79,80] and Java sparrows
[81] have shown the ability to discriminate between spoken
sentences in different languages and to generalize this discrimination to novel sentences. Zebra finches use pitch, duration and
amplitude to discriminate prosodic patterns, and they can generalize specific prosodic patterns of speech syllables to novel
syllables [36]. Further exploration of non-human species’ sensitivity to melodic aspects of speech may be a fruitful approach to
the study of some aspects of musicality.
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Evidence of relative pitch processing with sounds presented
sequentially rather than simultaneously is less promising. Starlings, brown-headed cowbirds (Molothrus ater), and northern
mockingbirds (Mimus polyglottos) were trained to discriminate ascending from descending note patterns [63–67].
However, they failed to generalize these patterns to novel
pitch levels when the altered patterns were outside the training
range, although they could quickly learn to do so. In general, it
appeared that the birds encoded both absolute and relative
pitch information in discriminating the patterns but depended
more on absolute information. Another set of studies trained
zebra finches and black-capped chickadees to discriminate
sets of pitches based on either their pitch ratios (i.e. relative
pitch) or their absolute frequencies. Both species learned the discrimination more quickly when there was a simple relative
pitch rule that they could use, although the discrimination
was quite difficult for the birds in comparison with learning a
simple absolute pitch rule. In short, these birds can engage in
relative pitch processing although they rely primarily on the
absolute pitch of sounds [68,69]. In one study, a bottlenose dolphin learned to respond to descending pitch contours, and after
extensive training, generalized that response to descending
pitch contours regardless of the component pitches [70].
In general, non-human species recognize the relative pitch
patterns of single chords more readily than those of note
sequences. Three factors may be implicated. First, the component frequencies of chords give rise to qualities such as
sensory consonance and dissonance [71] that contribute to
their distinctiveness. Second, chords, as single events, pose
fewer memory demands than sequences of notes. Third,
there are suggestions that harmonic (simultaneous) pitch
ratios are processed at early stages of the auditory cortical
pathway in rhesus macaques [72]. As a result, the pitch
ratios of chords or simultaneously presented notes may be
processed more automatically and therefore compared more
readily than the pitch ratios of melodic sequences.
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4. Importance of natural behaviour
(a) Incorporating naturalistic stimuli into
experimental work
As noted, laboratory research with artificial stimuli revealed
that birds focus on absolute aspects of pitch rather than relative
pitch [63–69], but evidence from field studies suggests otherwise. For example, fieldwork with black-capped chickadees
has shown that they produce a simple two-note tonal song
that can be sung at different absolute pitches, but maintains
its relative pitch ratio [86]. Moreover, this relative pitch ratio
is produced more accurately by dominant males [87], and accurately produced song pitch ratios are preferred by females [88].
These findings prompted laboratory research on this issue with
chickadees [89]. Chickadees were trained to discriminate pitch
ratios presented at different absolute frequencies, and made
use of this relevant song pitch ratio. An experimental group
was trained to respond to the pitch ratio from chickadee
song and not to respond to two non-chickadee-song pitch
ratios. A control group was trained to respond to a nonchickadee-song pitch ratio and not respond to two different
non-chickadee-song pitch ratios. The chickadees that were
required to identify the pitch ratio of their song learned the
task more quickly than the control group, suggesting that it
was easier for the chickadees to learn to discriminate the natural song pitch ratio than other pitch ratios [89]. A related study
showed that starlings that were trained to discriminate conspecific vocalizations were able to maintain that discrimination
even when the songs were transposed (i.e. pitches changed,
but pitch relations preserved) [90], raising the possibility that
absolute pitch processing has priority over relative pitch
processing only with stimuli lacking in ecological validity.
There are parallels in the realm of rhythm perception.
Although pigeons have difficulty with rhythm perception
tasks involving artificial stimuli [14], the natural coo vocalizations of pigeons and doves, neither of which are vocal
learners, are rhythmic. The collared dove produces a coo that
consists of five elements of different duration: three notes separated by two silences [91]. Playback experiments in the field
show that replacing the second or third note of the coo by
silence caused little change in the behavioural response to the
coo. When the removed note was not replaced by silence, shortening the duration of the coo, or when the pauses before and
after the second note were reversed, the response was significantly reduced. This suggested a sensitivity to the overall
(b) Music-like features in natural behaviour
The two best known features of musicality found in distantly
related species are vocal learning and entrainment (see glossary, table 1). There are suggestions that the two abilities are
related [94]. To date, the species that have been shown to
exhibit both vocal learning and entrainment are distantly
related to humans. Figure 1 shows the relatedness of various
vertebrate species, indicating which have vocal learning and
entrainment abilities.
The greatest focus has been on vocal learning, with much
greater concern for its relevance to language acquisition [95]
than to musicality. However, vocal learning is also relevant
to music production. For example, consider the extensive
research of Nicolai [96,97] on vocal learning in the bullfinch
(Pyrrhula pyrrhula), a songbird. Although bullfinches normally
learn their species-specific songs from conspecifics, they were
trained to sing folk melodies whistled to them. One bullfinch
learned a 45-note tune from a human tutor and sang it in
transposition (i.e. at a different pitch level), indicating exceptional vocal learning and relative pitch processing skills, also
incorporating appropriate rhythm. Other bullfinches alternated parts with the human tutor, as in antiphonal singing,
indicating that they anticipated as well as followed the notes
of a learned melody. Experiments such as these build on the
natural abilities of animals, as revealed by field research,
productively extending them to controlled contexts.
Snowball, the sulfur-crested cockatoo (Cacatua galerita
eleonora) whose dance video became a YouTube sensation,
helped renew scientific interest in entrainment in nonhuman species. Systematic study revealed that Snowball
could synchronize his movements to the beat of music and
adjust his rate of movement to changes in tempo [98], challenging the notion that entrainment is uniquely human. The
authors suggested, moreover, that such entrainment might
be evident in other species of vocal learners. In fact, a study
of YouTube videos featuring animal ‘dancing’ provided confirmation of entrainment to music in vocal learning species
but not in other species (e.g. dogs [12]). Another consistent
finding was successful training of a budgerigar (Melopsittacus
undulates) to tap along with a beat [99].
That only vocal learners have the capacity for entrainment
seems reasonable, given that the three avian groups in which
vocal learning has evolved independently have similar functional neural pathways that are not shared with non-vocal
learners, and are comparable to humans [100]. That is, they
have a direct connection between auditory perception areas
and motor areas [101]. Entrainment may necessitate this
kind of neural architecture [94]. At the same time, Schachner
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Phil. Trans. R. Soc. B 370: 20140094
Laboratory experiments with artificial stimuli have been helpful
in revealing perceptual skills and perceptual–motor coordination in non-human species. It is possible, however, that
their use may lead to underestimates of ability. One alternative
or supplementary approach is to use biologically relevant
stimuli in laboratory studies. Another is to study music-like
features in the natural behaviour (e.g. vocalizations) of animals.
rhythmic structure of the coos [92]. Although rhythm perception in doves may be closely tied to properties of their natural
coos, it is important to explore sensitivity to rhythms in patterns
that share at least some properties with natural vocalizations. In
another study, zebra finches were trained to discriminate conspecific songs and subsequently tested with novel versions
that altered amplitude, fundamental frequency or duration
[93]. Although performance decreased substantially with
changes in amplitude or fundamental frequency, it was maintained with duration changes of over 25%, well beyond zebra
finches’ reported sensitivity to temporal changes [13]. The
implication is that the rhythmic patterning is particularly
important for pattern classification in zebra finches.
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plasticity of their nervous system [85]. By using these animals
as models, we can gain information about the neural activity
(e.g. through electrophysiological recordings) as well as
manipulations (e.g. pharmacology, electric-stimulation, optogenetics) that can alter brain mechanisms and corresponding
behaviour, facilitating our understanding of the neural
underpinnings of musicality in humans.
amphibians
reptiles
birds
songbirds
parrots
hummingbirds
non-primate mammals
sea lions
cetaceans
bats
elephants
New World monkeys
Old World monkeys
humans
Figure 1. Species with vocal learning and entrainment abilities and their relationship in a phylogenetic tree.
et al. [12] found evidence for entrainment in only one of the
avian vocal learning subgroups, the parrot species, and not
in songbirds. The only non-parrot species in which entrainment has been detected to date is elephants. Although
elephants show evidence of vocal learning [11] their vocal
learning mechanism is unknown, but is likely to differ from
that of parrots. A compelling recent study showed that a California sea lion (Zalophus californianus) could also be trained to
synchronize with a beat, and then spontaneously generalized
to music [102]. This species is not thought to be a vocal learner, although some other pinnipeds are vocal learners [11]. It
is possible that sea lions have vocal learning abilities that are
as yet unknown. However, it could also be that the ability to
synchronize with a beat only requires part of what is required
for vocal learning, or even that entrainment abilities can occur
without any of the components for vocal learning. Another
recent study showed that a chimpanzee, one of the closest
non-vocal learning relatives of humans, spontaneously
entrained to a beat while completing a motor tapping task
[103]. Clearly, the proposed connection between vocal learning and entrainment [94] requires further research with
species that are not vocal learners.
If entrainment is defined more broadly, it could include
many non-vocal learning species such as several species of
fireflies synchronizing flashing with one another [104], and
several species of frogs [105] and katydids [106] synchronizing their chorusing. Identifying a pulse and locking in
phase with it is a simpler task than detecting and entraining
to a beat within a stream of music, where the beat is not
always marked with an acoustic event, and other acoustic
events are present between beats (see [94] for review). Understanding the range of natural abilities related to entrainment
could clarify what is relevant for musicality.
There are other potentially productive means of studying the
precursors of musicality in non-human species. One approach is
to search for music-like features in animal vocalizations. For
example, Araya-Salas [107] examined whether the pitch ratios
created by adjacent notes of the song of nightingale wrens
(Microcerculus philomela) conform to harmonic pitch ratios.
From 243 comparisons, only six were significantly close to
harmonic pitch ratios, suggesting no consistent use of harmonic pitch ratios. Another approach builds on the studies by
Hartshorne [108] and others in seeking ‘aesthetic’ features in
natural birdsong that might have arousing or emotive consequences, as music does for human listeners. This notion was
met with considerable scepticism, but Rothenberg et al. [109]
posed a similar question with thrush nightingales (Luscinia luscinia). According to their analysis, the songs of thrush nightingales
have similar patterns of tension and resolution to those of music,
which create expectation and anticipation in human listeners. If a
certain level of familiarity and novelty is valued across species
that produce complex songs, this could lead to insights into
the origins of our motivation for music.
Another route to discovering music-like behaviours in
non-human species is to make predictions from the natural
behaviour of humans. For example, humans generalize across
timbres, recognizing a melody, regardless of the instrument on
which it is played. In most cases, it makes sense not to generalize
across timbres. Different spectral information can change the
meaning of vocalizations not only in human speech with different vowels, but also in animal vocalizations [110]. A study
species that may be more fruitful for timbre generalization
research would be a species that mimics the vocalizations of
other species. For satin bowerbirds (Ptilonorhynchus violaceus)
female preference for mates and male mate success may
depend on the accuracy with which males imitate heterospecific
vocalizations [111]. If the mimetic accuracy is what is important,
and not simply how well-learned a song is (as has been shown to
be important in other species, [112]), female bowerbirds would
need to assess the original heterospecific vocalization, and the
conspecific imitation, in a way that is similar to a human evaluating a singer’s performance in comparison with a pianist. She
would need to be able to distinguish the two, but also generalize
between them in the sense that she is aware that they are meant
to be the same thing. In short, reflecting on natural human and
non-human behaviours that are musically relevant can provide
ideas about species and abilities that offer promising directions
for comparative study.
(c) Integrating natural and artificial studies
Naturalistic studies have revealed important abilities and
questions related to the biological basis of music such as
vocal learning and entrainment. They have also suggested
new directions for laboratory research.
Laboratory studies often reveal abilities that are not used
by non-human species under natural conditions. Knowledge
of the underlying capacity for those abilities can contribute
to an understanding of their evolutionary, developmental
and physiological foundations. The capacity for a particular
ability, even if it is unrealized in nature, may arise from the
evolutionary history of the species. Identifying the
Phil. Trans. R. Soc. B 370: 20140094
non-human apes
6
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vo
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en earn
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en
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At present, there is limited laboratory research on the components of musicality in non-human species although there is
increasing interest in this domain, so considerable expansion
of this research direction is likely. As noted, traditional laboratory studies and naturalistic studies can provide equally
important and complementary insights into musically relevant skills. One example noted earlier was finer pitch
[46–49] and temporal [13] resolution in birds than in mammals, which emerged from laboratory studies, and vocal
learning and entrainment abilities in some bird and mammal
species [11–12,94], which emerged from naturalistic studies.
Currently, vocal learning and entrainment are the principal
focus of research on musically related behaviours and their
underpinnings in non-human species. There are other potentially productive questions that could be pursued. For
example, what kinds of behaviour require relative pitch
Acknowledgements. We thank everyone who attended the ‘What makes us
musical animals? Cognition, biology and the origins of musicality’
workshop for the stimulating meeting that led to this special issue,
especially Henkjan Honing for organizing the meeting and the other
attendees that participated in the discussion relating directly to this
paper on natural versus artificial studies of animal music perception, including Peter Tyack and Aniruddh Patel. We thank Sandra
Trehub for her very detailed revisions as editor, and the anonymous
reviewers for their insights on paper organization. We thank also
Daniel L. Bowling for help drawing the figure.
Author contributions. M.H. wrote the majority of the initial draft and revision of the paper while integrating several paragraphs from C.t.C.
and H.M. This paper is based on a review talk on ‘Animal music perception’ by M.H., an introduction from C.t.C to the ‘What makes us
musical animals? Cognition, biology and the origins of musicality’
workshop, and a discussion involving all authors. All authors contributed to the ideas and framework contained within the paper
and edited the manuscript.
Funding statement. M.H. was supported by a European Research Council
advanced grant (no. 230604 ‘SOMACCA’) awarded to W. Tecumseh
Fitch at the University of Vienna during the initial submission of this
manuscript and is currently supported by a Banting Postdoctoral Fellowship awarded by the Natural Sciences and Engineering Research
Council of Canada hosted by the University of Vienna. H.M. is supported by PAPIIT IN201214-25 and CONACYT 151223. Y.K. is
currently supported by a contract from the National Institutes of
Health, BBSRC (BB/J009849/1) and Wellcome Trust (WT102961/Z/
13/Z) grants to C. Petkov at Newcastle University. Y.H. is supported
by a grant-in-aid for Young Scientists (B) (26730074) from the Japan
Society for the Promotion of Science (JSPS).
Competing interests. The authors have no competing interests.
References
1.
2.
3.
4.
5.
6.
7.
Honing H, ten Cate C, Peretz I, Trehub SE. 2015
Without it no music: cognition, biology and
evolution of musicality. Phil. Trans. R. Soc. B 370,
20140088. (doi:10.1098/rstb.2014.0088)
Porter D, Neuringer A. 1984 Music discriminations
by pigeons. J. Exp. Psychol. Anim. B 10, 138–148.
(doi:10.1037/0097-7403.10.2.138)
Chase AR. 2001 Music discriminations by carp
(Cyprinus carpio). Anim. Learn. Behav. 29,
336–353. (doi:10.3758/BF03192900)
Herrnstein RJ, Loveland DH. 1964 Complex visual
concept in a pigeon. Science 146, 549–551.
(doi:10.1126/science.146.3643.549)
Weisman RG, Spetch ML. 2010 Determining
when birds perceive correspondence between pictures
and objects: a critique. Comp. Cogn. Behav. Rev. 5,
117–131. (doi:10.3819/ccbr.2010.50006)
Mingle ME, Eppley TM, Campbell MW, Hall K, Horner
V, de Waal FBM. 2014 Chimpanzees prefer African and
Indian music over silence. J. Exp. Psychol. Anim. B 40,
502–505. (doi:10.1037/xan0000032)
McDermott J, Hauser MD. 2007 Nonhuman primates
prefer slow tempos but dislike music overall.
Cognition 104, 654–668. (doi:10.1016/j.cognition.
2006.07.011)
8.
9.
10.
11.
12.
13.
14.
Chiandetti C, Vallortigara G. 2011 Chicks like
consonant music. Psychol. Sci. 22, 1270–1273.
(doi:10.1177/0956797611418244)
McDermott J, Hauser M. 2004 Are consonant
intervals music to their ears? Spontaneous acoustic
preferences in a nonhuman primate. Cognition 94,
B11 –B21. (doi:10.1016/j.cognition.2004.04.004)
Cook ND, Fujisawa TX. 2006 The psychophysics of
harmony perception: harmony is a three-tone
phenomenon. Empirical Mus. Rev. 1, 106–126.
Tyack PL. 2008 Convergence of calls as animals form
social bonds, active compensation for noisy
communication channels, and the evolution of vocal
learning in mammals. J. Comp. Psychol. 122,
319 –331. (doi:10.1037/a0013087)
Schachner A, Brady TF, Pepperberg IM, Hauser MD.
2009 Spontaneous motor entrainment to music in
multiple vocal mimicking species. Curr. Biol. 19,
831 –866. (doi:10.1016/j.cub.2009.03.061)
Dooling RJ, Leek MR, Gleich O, Dent ML. 2002
Auditory temporal resolution in birds: discrimination
of harmonic complexes. J. Acoust. Soc. Am. 112,
748 –759. (doi:10.1121/1.1494447)
Hagmann CE, Cook RG. 2010 Testing meter, rhythm,
and tempo discriminations in pigeons. Behav.
15.
16.
17.
18.
19.
20.
Process 85, 99 –110. (doi:10.1016/j.beproc.2010.
06.015)
Hulse SH, Humpal J, Cynx J. 1984 Discrimination
and generalization of rhythmic and arrhythmic
sound patterns by European starlings (Sturnus
vulgaris). Music Percept. 1, 442– 464. (doi:10.2307/
40285272)
Janata P, Grafton ST. 2003 Swinging in the brain:
shared neural substrates for behaviors related to
sequencing and music. Nat. Neurosci. 6, 682 –687.
(doi:10.1038/nn1081)
Grahn JA, Brett M. 2007 Rhythm and beat
perception in motor areas of the brain. J. Cogn.
Neurosci. 19, 893–906. (doi:10.1162/jocn.2007.19.
5.893)
Grahn JA. 2009 The role of the basal ganglia in beat
perception. Ann. N.Y. Acad. Sci. 1169, 35 –45.
(doi:10.1111/j.1749-6632.2009.04553.x)
Zatorre RJ, Chen JL, Penhune VB. 2007 When the
brain plays music: auditory– motor interactions in
music perception and production. Nat. Rev. Neurosci.
8, 547 –558. (doi:10.1038/nrn2152)
Zarco W, Merchant H, Prado L, Mendez JC. 2009
Subsecond timing in primates: comparison of
interval production between human subjects and
7
Phil. Trans. R. Soc. B 370: 20140094
5. Conclusion
preferences like those present in chickadees [89]? What kinds
of behaviour require timbre generalization like that observed
in zebra finches [36–37]? Why is auditory grouping relevant
in some species? One way forward is to search for relevant natural behaviours in less studied species and to examine the natural
behaviours of species commonly studied in the laboratory.
rstb.royalsocietypublishing.org
requirements of such abilities and their evolutionary pressures
may be facilitated by studying the limits of these abilities.
There is increasing research on aspects of musicality in various non-human species, but it is rare to find naturalistic studies
of musically relevant abilities and studies of the limits of those
abilities in the same species. A rare but productive example of a
combined approach involves the chickadee, which has been the
subject of extensive field and laboratory research. This blend of
research methods made it possible to understand the relative
pitch processing skills of this species [69,86–89]. Comparably
important insights might arise from increased field research
with species that have received extensive experimental study
and increased laboratory research with species whose natural
behaviours have been well documented.
Downloaded from http://rstb.royalsocietypublishing.org/ on April 9, 2015
22.
23.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
thresholds in the white rat. J. Exp. Psychol. 33,
407–419. (doi:10.1037/h0057863)
Richards DG, Wolz JP, Herman LM. 1975 Vocal
mimicry of computer-generated sounds and vocal
labeling of objects by a bottlenosed dolphin,
Tursiops truncates. J. Comp. Psychol. 98, 10 –28.
(doi:10.1037/0735-7036.98.1.10)
Wright AA, Rivera JJ, Hulse SH, Shyan M, Neiworth
JJ. 2000 Music perception and octave generalization
in rhesus monkeys. J. Exp. Psychol. Gen. 129,
291–307. (doi:10.1037/0096-3445.129.3.291)
Cynx J. 1993 Auditory frequency generalization and a
failure to find octave generalization in a songbird, the
European starling (Sturnus vulgaris). J. Comp. Psychol.
107, 140–146. (doi:10.1037/0735-7036.107.2.140)
Hoeschele M, Weisman RG, Sturdy CB. 2012 Pitch
chroma discrimination, generalization, and transfer
tests of octave equivalence in humans. Attent.
Percept. Psychophys. 74, 1742–1760. (doi:10.3758/
s13414-012-0364-2)
Hoeschele M, Weisman RG, Guillette LM, Hahn AH,
Sturdy CB. 2013 Chickadees fail standardized
operant tests for octave equivalence. Anim. Cogn.
16, 599 –609. (doi:10.1007/s10071-013-0597-z)
Hulse SH, Bernard DJ, Braaten RF. 1995 Auditory
discrimination of chord-based spectral structures by
European starlings (Sturnus vulgaris). J. Exp. Psychol.
124, 409–423. (doi:10.1037/0096-3445.124.4.409)
Watanabe S, Uozumi M, Tanaka N. 2005
Discrimination of consonance and dissonance in
Java sparrows. Behav. Process 70, 203 –208.
(doi:10.1016/j.beproc.2005.06.001)
Izumi A. 2000 Japanese monkeys perceive sensory
consonance of chords. J. Acoust. Soc. Am. 108,
3073– 3078. (doi:10.1121/1.1323461)
Brooks DI, Cook RG. 2010 Chord discrimination by
pigeons. Music Percept. 27, 183–196. (doi:10.1525/
mp.2010.27.3.183)
Hoeschele M, Cook RG, Guillette LM, Brooks DI,
Sturdy CB. 2012 Black-capped chickadee (Poecile
atricapillus) and human (Homo sapiens) chord
discrimination. J. Comp. Psychol. 126, 57– 67.
(doi:10.1037/a0024627)
Hulse SH, Cynx J. 1985 Relative pitch perception is
constrained by absolute pitch in songbirds (Mimus,
Molothrus, and Sturnus). J. Comp. Psychol. 99,
176–196. (doi:10.1037/0735-7036.99.2.176)
Hulse SH, Cynx J. 1986 Interval and contour in serial
pitch perception by a passerine bird, the European
starling (Sturnus vulgaris). J. Comp. Psychol. 100,
215–228. (doi:10.1037/0735-7036.100.3.215)
Hulse SH, Cynx J, Humpal J. 1984 Absolute and
relative pitch discrimination in serial pitch
perception by birds. J. Exp. Psychol. 113, 38– 54.
(doi:10.1037/0096-3445.113.1.38)
Page SC, Hulse SH, Cynx J. 1989 Relative pitch
perception in the European starling (Sturnus
vulgaris): further evidence for an elusive
phenomenon. J. Exp. Psychol. Anim. B 15,
137–146. (doi:10.1037/0097-7403.15.2.137)
MacDougall-Shackleton SA, Hulse SH. 1996
Concurrent absolute and relative pitch processing by
European starlings (Sturnus vulgaris). J. Comp.
8
Phil. Trans. R. Soc. B 370: 20140094
24.
36.
discrimination in black-capped chickadees but not
humans. J. Comp. Psychol. 128, 387– 401. (doi:10.
1037/a0037159)
Spierings MJ, ten Cate C. 2014 Zebra finches are
sensitive to prosodic features of human speech.
Proc. R. Soc. B 281, 20140480. (doi:10.1098/rspb.
2014.0480)
Ohms VR, Gill A, Van Heijningen CAA, Beckers GJL, ten
Cate C. 2010 Zebra finches exhibit speaker-independent
phonetic perception of human speech. Proc. R. Soc. B
277, 1003–1009. (doi:10.1098/rspb.2009.1788)
Dowling WJ, Harwood DL. 1986 Music cognition.
Orlando, FL: Academic Press Inc.
Oxenham AJ. 2012 Pitch perception. J. Neurosci. 32,
13 335–13 338. (doi:10.1523/JNEUROSCI.3815-12.2012)
Lau BK, Werner LA. 2012 Perception of missing
fundamental pitch by 3- and 4-month-old human
infants. J. Acoust. Soc. Am. 132, 3874–3882.
(doi:10.1121/1.4763991)
Heffner H, Whitfield IC. 1976 Perception of the
missing fundamental by cats. J. Acoust. Soc. Am.
59, 915– 919. (doi:10.1121/1.380951)
Tomlinson RWW. 1988 Perception of the missing
fundamental in nonhuman primates. J. Acoust. Soc.
Am. 84, 560 –565. (doi:10.1121/1.396833)
Cynx J, Shapiro M. 1986 Perception of missing
fundamental by a species of songbird (Sturnus
vulgaris). J. Comp. Psychol. 100, 356 –360. (doi:10.
1037/0735-7036.100.4.356)
Ward WD. 1999 Absolute pitch. In The psychology of
music (ed. D Deutsch), pp. 265–298, 2nd edn.
San Diego, CA: Academic Press.
Schellenberg EG, Trehub SE. 2003 Good pitch
memory is widespread. Psychol. Sci. 14, 262–266.
(doi:10.1111/1467-9280.03432)
Weisman R, Njegovan M, Sturdy CB, Phillmore L,
Coyle J, Mewhort D. 1998 Frequency-range
discriminations: special and general abilities in
zebra finches (Taeniopygia guttata) and humans
(Homo sapiens). J. Comp. Psychol. 112, 244–258.
(doi:10.1037/0735-7036.112.3.244)
Weisman RG, Njegovan MG, Williams MT, Cohen JS,
Sturdy CB. 2004 A behavior analysis of absolute
pitch: sex, experience, and species. Behav. Process.
66, 289– 307. (doi:10.1016/j.beproc.2004.03.010)
Friedrich A, Zentall T, Weisman R. 2007 Absolute
pitch: frequency-range discriminations in pigeons
(Columba livia)– comparisons with zebra finches
(Taeniopygia guttata) and humans (Homo sapiens).
J. Comp. Psychol. 121, 95– 105. (doi:10.1037/07357036.121.1.95)
Weisman RG, Balkwill L-L, Hoeschele M, Moscicki
MK, Bloomfield LL, Sturdy CB. 2010 Absolute
pitch in boreal chickadees and humans: exceptions
that test a phylogenetic rule. Learn. Motiv. 41,
156 –173. (doi:10.1016/j.lmot.2010.04.002)
Burns EM. 1999 Intervals, scales, and tuning. In The
psychology of music (ed. D Deutsch), pp. 215– 264,
2nd edn. San Diego, CA: Academic Press.
Patel AD. 2003 Language, music, syntax and the brain.
Nat. Neurosci. 6, 674–681. (doi:10.1038/nn1082)
Blackwell HR, Schlosberg H. 1943 Octave
generalization, pitch discrimination, and loudness
rstb.royalsocietypublishing.org
21.
rhesus monkeys. J. Neurophysiol. 106, 3191 –3202.
(doi:10.1152/jn.00066.2009)
Mendez JC, Prado L, Mendoza G, Merchant H. 2010
Temporal and spatial categorization in human and
non-human primates. Front. Integr. Neurosci. 5, 50.
Merchant H, Battaglia-Mayer A, Georgopoulos AP.
2003 Interception of real and apparent motion
targets: psychophysics in humans and monkeys.
Exp. Brain Res. 152, 106– 112. (doi:10.1007/
s00221-003-1514-5)
Merchant H, Zarco W, Pe´rez O, Prado L, Bartolo R.
2011 Measuring time with different neural
chronometers during a synchronization-continuation
task. Proc. Natl Acad. Sci. USA 108, 19 784–19 789.
(doi:10.1073/pnas.1112933108)
Hikosaka O, Rand M, Nakamura K, Miyachi S,
Kitaguchi K, Sakai K, Shimo Y. 2002 Long-term
retention of motor skill in macaque monkeys and
humans. Exp. Brain Res. 147, 494 –504. (doi:10.
1007/s00221-002-1258-7)
Hikosaka O, Nakamura K, Sakai K, Nakahara H. 2002
Central mechanisms of motor skill learning. Curr.
Opin. Neurobiol. 12, 217–222. (doi:10.1016/S09594388(02)00307-0)
Tanji J. 2001 Sequential organization of multiple
movements: involvement of cortical motor areas.
Annu. Rev. Neurosci. 24, 631– 651. (doi:10.1146/
annurev.neuro.24.1.631)
Macar F, Coull J, Vidal F. 2006 The supplementary
motor area in motor and perceptual time
processing: fMRI studies. Cogn. Process 7, 89 –94.
(doi:10.1007/s10339-005-0025-7)
Mita A, Mushiake H, Shima K, Matsuzaka Y, Tanji J.
2009 Interval time coding by neurons in the
presupplementary and supplementary motor areas.
Nat. Neurosci. 12, 502–507. (doi:10.1038/nn.2272)
Merchant H, Pe´rez O, Zarco W, Ga´mez J. 2013 Interval
tuning in the primate medial premotor cortex as a
general timing mechanism. J. Neurosci. 33, 9082–9096.
(doi:10.1523/JNEUROSCI.5513-12.2013)
Amagai S, Dooling RJ, Shamma S, Kidd TL, Lohr B.
2000 Detection of modulation in spectral envelopes
and linear-rippled noises by budgerigars
(Melopsittacus undulatus). J. Acoust. Soc. Am. 105,
2029–2035. (doi:10.1121/1.426736)
Lohr B, Dooling RJ. 1998 Detection of changes in
timbre and harmonicity in complex sounds by zebra
finches (Taeniopygia guttata) and budgerigars
(Melopsittacus undulatus). J. Comp. Psychol. 112,
36 –47. (doi:10.1037/0735-7036.112.1.36)
Cynx J, Williams H, Nottebohm F. 1990 Timbre
discrimination in zebra finch (Taeniopygia guttata)
song syllables. J. Comp. Psychol. 104, 303 –308.
(doi:10.1037/0735-7036.104.4.303)
Warker JA, Halpern AR. 2005 Musical stem
completion: humming that note. Am. J. Psychol.
118, 567–585.
Ha´den GP, Stefanics G, Vestergaard MD, Denham SL,
Sziller I, Winkler I. 2009 Timbre-independent extraction
of pitch in newborn infants. Psychophysiology 46, 69–
74. (doi:10.1111/j.1469-8986.2008.00749.x)
Hoeschele M, Cook RG, Guillette LM, Hahn AH,
Sturdy CB. 2014 Timbre influences chord
Downloaded from http://rstb.royalsocietypublishing.org/ on April 9, 2015
69.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
84.
85.
86.
87.
88.
89.
90.
91.
92.
93.
94.
95.
96.
97.
98.
99.
100.
101.
102.
103.
104.
105.
106.
107.
108.
109.
110.
111.
112.
(Pyrrhula pyrrula) gives hints about a cognitive note
sequence processing. Anim. Cogn. 17, 143–155.
(doi:10.1007/s10071-013-0647-6)
Patel AD, Iversen JR, Bregman MR, Schulz I. 2009
Experimental evidence for synchronization to a
musical beat in a nonhuman animal. Curr. Biol. 19,
827–830. (doi:10.1016/j.cub.2009.03.038)
Hasegawa A, Okanoya K, Hasegawa T, Seki Y. 2011
Rhythmic synchronization tapping to an audio–
visual metronome in budgerigars. Sci. Rep. 1, 120.
(doi:10.1038/srep00120)
Jarvis ED. 2004 Learned birdsong and the
neurobiology of human language. Ann. N.Y. Acad.
Sci. 1016, 749–777. (doi:10.1196/annals.1298.038)
Feenders G, Liedvogel M, Rivas M, Zapka M, Horita
H, Hara E, Jarvis ED. 2008 Molecular mapping of
movement-associated areas in the avian brain: a
motor theory for vocal learning origin. PLoS ONE 3,
e1768. (doi:10.1371/journal.pone.0001768)
Cook P, Rouse A, Wilson M, Reichmuth C. 2013 A
California sea lion (Zalophus californianus) can keep
the beat: motor entrainment to rhythmic auditory
stimuli in a non vocal mimic. J. Comp. Psychol. 127,
412–427. (doi:10.1037/a0032345)
Hattori Y, Tomonaga M, Matsuzawa T. 2013
Spontaneous synchronized tapping to an auditory
rhythm in a chimpanzee. Sci. Rep. 3, 1566. (doi:10.
1038/srep01566)
Buck J. 1988 Synchronous rhythmic flashing in
fireflies. II. Quart. Rev. Biol. 63, 265–289. (doi:10.
1086/415929)
Gerhardt HC, Huber F. 2002 Acoustic communication
in insects and anurans. Chicago, IL: University of
Chicago Press.
Greenfield MD, Schul J. 2008 Mechanisms and
evolution of synchronous chorusing: emergent
properties and adaptive functions in Neoconocephalus
katydids (Orthoptera: Tettigoniidae). J. Comp. Psychol.
122, 289–297. (doi:10.1037/0735-7036.122.3.289)
Araya-Salas M. 2012 Is birdsong music? Evaluating
harmonic intervals in songs of a neotropical
songbird. Anim. Behav. 84, 309 –313. (doi:10.1016/
j.anbehav.2012.04.038)
Hartshorne C. 1973 Born to sing; an interpretation
and world survey of bird song. Bloomington, IN:
Indiana University Press.
Rothenberg D, Roeske TC, Voss HU, Naguib M,
Tchernichovski O. 2014 Investigation of musicality in
birdsong. Hear. Res. 308, 71 –83. (doi:10.1016/j.
heares.2013.08.016)
Templeton CN, Greene E, Davis K. 2005 Allometry of
alarm calls: black-capped chickadees encode
information about predator size. Science 308,
1934– 1937. (doi:10.1126/science.1108841)
Coleman SW, Patricelli GL, Coyle B, Siani J, Borgia G.
2007 Female preferences drive the evolution of
mimetic accuracy in male sexual displays. Biol. Lett.
3, 463 –466. (doi:10.1098/rsbl.2007.0234)
Nowicki SW, Searcy A, Peters S. 2002 Quality of
song learning affects female response to male bird
song. Proc. R. Soc. Lond. B 269, 1949–1954.
(doi:10.1098/rspb.2002.2124)
9
Phil. Trans. R. Soc. B 370: 20140094
70.
83.
rhythmic task. J. Neurophysiol. 111, 2138–2149.
(doi:10.1152/jn.00802.2013)
Repp BH. 2005 Sensorimotor synchronization: a
review of the tapping literature. Psychon. Bull. Rev.
12, 969– 992. (doi:10.3758/BF03206433)
Merchant H, Honing H. 2014 Are non-human
primates capable of rhythmic entrainment?
Evidence for the gradual audiomotor evolution
hypothesis. Front. Neurosci. 7, 274. (doi:10.3389/
fnins.2013.00274)
Mendoza G, Merchant H. 2014 Motor system
evolution and the emergence of high cognitive
functions. Prog. Neurobiol. 122C, 73 –93.
Weisman R, Ratcliffe L, Johnsrude I, Hurly TA. 1990
Absolute and relative pitch production in the song
of the black-capped chickadee. Condor 92,
118 –124. (doi:10.2307/1368390)
Christie PJ, Mennill DJ, Ratcliffe LM. 2004 Pitch
shifts and song structure indicate male quality in
the dawn chorus of black-capped chickadees. Behav.
Ecol. Sociobiol. 55, 341 –348. (doi:10.1007/s00265003-0711-3)
Weisman R, Ratcliffe L. 2004 Relative pitch and the
song of black-capped chickadees. Am. Sci. 92,
532 –539. (doi:10.1511/2004.6.532)
Hoeschele M, Guillette LM, Sturdy CB. 2012 Biological
relevance of acoustic signal affects discrimination
performance in a songbird. Anim. Cogn. 15, 677–688.
(doi:10.1007/s10071-012-0496-8)
Bregman MR, Patel AD, Gentner TQ. 2012 Stimulusdependent flexibility in non-human auditory pitch
processing. Cognition 122, 51– 60. (doi:10.1016/j.
cognition.2011.08.008)
Ballintijn MR, ten Cate C. 1999 Variation in number
of elements in the perch-coo vocalization of the
collared dove (Streptopelia decaocto) and what it
may tell about the sender. Behaviour 136,
847 –864. (doi:10.1163/156853999501603)
Slabbekoorn H, ten Cate C. 1999 Collared dove
responses to playback: slaves to the rhythm.
Ethology 105, 377–391. (doi:10.1046/j.1439-0310.
1999.00420.x)
Nagel KI, McLendon HM, Doupe AJ. 2010
Differential influence of frequency, timing, and
intensity cues in a complex acoustic categorization
task. J. Neurophysiol. 104, 1426 –1437. (doi:10.
1152/jn.00028.2010)
Patel AD, Iversen JR, Bregman MR, Schulz I. 2009
Studying synchronization to a musical beat in
nonhuman animals. Ann. N.Y. Acad. Sci. 1169,
459 –469. (doi:10.1111/j.1749-6632.2009.04581.x)
Doupe AJ, Kuhl PK. 1999 Birdsong and human speech:
common themes and mechanisms. Annu. Rev. Neurosci.
22, 567–631. (doi:10.1146/annurev.neuro.22.1.567)
Gu¨ttinger HR, Turner T, Dobmeyer S, Nicolai J. 2002
Melodiewahrnehmung und Wiedergabe beim
Gimpel: Untersuchungen an liederpfeifenden und
Kanariengesang imitierenden Gimpeln (Pyrrhula
pyrrhula). J. Ornithol. 143, 303–318. (doi:10.1007/
BF02465481)
Nicolai J, Gundacker C, Teeselink K, Gu¨ttinger HR.
2014 Human melody singing by bullfinches
rstb.royalsocietypublishing.org
68.
Psychol. 110, 139–146. (doi:10.1037/0735-7036.
110.2.139)
Weisman RG, Njegovan M, Ito S. 1994 Frequency
ratio discrimination by zebra finches (Taeniopygia
guttata) and humans (Homo sapiens). J. Comp.
Psychol. 108, 363–372. (doi:10.1037/0735-7036.
108.4.363)
Njegovan M, Weisman R. 1997 Pitch discrimination
in field- and isolation-reared black-capped
chickadees (Parus atricapillus). J. Comp. Psychol.
111, 294–301. (doi:10.1037/0735-7036.111.3.294)
Ralston JV, Herman LM. 1995 Perception and
generalization of frequency contours by a bottlenose
dolphin (Tursiops truncatus). J. Comp. Psychol. 109,
268–277. (doi:10.1037/0735-7036.109.3.268)
Helmholtz HLF. 1877 On the sensations of tone as a
physiological basis for the theory of music.
New York, NY: Dover Publications.
Kikuchi Y, Horwitz B, Mishkin M, Rauschecker JP.
2014 Processing of harmonics in the lateral belt of
macaque auditory cortex. Front. Neurosci. 8, 204.
(doi:10.3389/fnins.2014.00204)
Woodrow H. 1909 A quantitative study of rhythm:
the effect of variations in intensity, rate and
duration. Arch. Psychol. 14, 1– 66.
Bion R, Benavides-Varela S, Nespor M. 2011
Acoustic markers of prominence influence infants’
and adults’ segmentation of speech sequences.
Lang. Speech 54, 123–140. (doi:10.1177/
0023830910388018)
de la Mora DM, Nespor M, Toro JM. 2013 Do
humans and nonhuman animals share the grouping
principles of the iambic –trochaic law? Attent.
Percept. Psychophys. 75, 92 –100. (doi:10.3758/
s13414-012-0371-3)
Cruttenden A. 1981 Falls and rises: meanings and
universals. J. Linguist. 17, 77 –91. (doi:10.1017/
S0022226700006782)
Cutler A, Dahan D, van Donselaar W. 1997 Prosody
in the comprehension of spoken language: a
literature review. Lang. Speech 40, 140 –201.
Tincoff R, Hauser M, Tsao F, Spaepen G, Ramus F,
Mehler J. 2005 The role of speech rhythm in
language discrimination: further tests with a nonhuman primate. Dev. Sci. 8, 26 –35. (doi:10.1111/j.
1467-7687.2005.00390.x)
Toro JM, Trobalon JB, Sebastian-Galles N. 2003 The
use of prosodic cues in language discrimination
tasks by rats. Anim. Cogn. 6, 131 –136. (doi:10.
1007/s10071-003-0172-0)
Toro JM, Trobalon JB, Sebastian-Galles N. 2005 Effects
of backward speech and speaker variability in
language discrimination by rats. J. Exp. Psychol. Anim.
B 31, 95–100. (doi:10.1037/0097-7403.31.1.95)
Naoi N, Watanabe S, Maekawa K, Hibiya J. 2012
Prosody discrimination by songbirds (Padda
oryzivora). PLoS ONE 7, e47446. (doi:10.1371/
journal.pone.0047446)
Donnet S, Bartolo R, Fernandes JM, Cunha JPS,
Prado L, Merchant H. 2014 Monkeys time their
pauses of movement and not their movementkinematics during a synchronization-continuation